AI tools for “ui”

…EFS, SMB or S3 volume, or which of these options fits a…

…stats; create or iterate container artifacts; build images server-side; lock artifacts for production; zero-downtime rolling artifact…

…including Python SDK, dr-cli, Agent Assist, and all required dependencies. Use when the user has not yet worked with DataRobot on this machine, OR when any DataRobot task fails due to missing or invalid…

Tools and guidance for making predictions with DataRobot deployments, including real-time predictions, batch scoring, prediction dataset generation, and prediction explanations (SHAP/XEMP). Use when making predictions,…

Comprehensive guidance for training models in DataRobot, including project creation, AutoML configuration, feature engineering, and model selection. Use when training models, creating AutoML projects, or selecting…

Tools and guidance for monitoring model performance, tracking data drift, managing model health, and detecting prediction anomalies. Use when monitoring deployed models, tracking drift, or investigating prediction…

Tools and guidance for model explainability, prediction explanations, feature impact analysis, SHAP values, SHAP distributions, anomaly assessment, and model diagnostics. Use when analyzing model explanations, feature…

Tools and guidance for deploying DataRobot models, managing deployments, configuring prediction environments, and deployment operations. Use when deploying models, creating or updating deployments, or configuring…

…wants to assess whether an AI agent repository (DataRobot-built or not) is enterprise-ready, run a gap analysis / readiness scan against security, governance, reliability, or regulatory standards, score an agent…

Guidance for feature engineering, feature discovery, feature importance analysis, and understanding DataRobot's automated feature engineering capabilities. Use when working with feature engineering, feature discovery,…

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Tools and guidance for data upload, dataset management, data validation, and preparing data for DataRobot projects. Use when uploading datasets, managing data, or validating data for DataRobot.

…Creating a connection happens in the DataRobot…

Guidance for setting up CI/CD pipelines for DataRobot application templates using GitLab, GitHub Actions, and Pulumi for infrastructure as code. Use when setting up CI/CD pipelines, configuring deployments, or managing…

…the project has no `infra/Pulumi.yaml`. Not for agents built from the agent template, which deploy with Pulumi through datarobot-agent-assist. Users usually just say "deploy" or "deploy to DataRobot" and won't…

Use when the user wants to design, build, code, or deploy an AI agent on DataRobot; mentions agent_spec.yaml, dress rehearsal, the DataRobot agent template, LangGraph, CrewAI, LlamaIndex, NAT, Base agents, MCP servers,…

Use when the user wants to design, build, code, simulate, or deploy an AI agent (not a predictive model) to DataRobot; mentions agent_spec.yaml, dr-assist, datarobot-agent-assist, dress rehearsal, swarm simulation, or…

…disclosure, or should be chunked without changing…

…Datadog data-domain skill directs you to visualization guidance. This is the plugin's local copy of the `datadog/visualizations` server skill; prefer it over fetching the server…

…use action words like "create", "scaffold", "new", or "build" together with "Datadog App" or "@datadog/apps" or "npm create @datadog/apps". Do NOT use for any question that does not involve creating a new project…